Data science

Data Science, also known as data-driven science, dealing with unstructured and structured data,
and it is a large field covering everything from data collection, cleaning, standardization, analysis,
visualization and reporting. Data Science is the combination of statistics, mathematics,
programming, problem-solving, capturing data in ingenious ways, the ability to look at things
differently, and the activity of cleansing, preparing and aligning the data. The main 3 components
involved in data science are organising, packaging and delivering data.

Applications of Data Science:

Internet search:
Search engines make use of data science algorithms to deliver best results
for search queries in a fraction of seconds.

Recommender systems:
The recommender systems not only make it easy to find relevant
products from billions of products available but also adds a lot to user-experience. A lot of
companies use this system to promote their products and suggestions in accordance with the
user’s demands and relevance of information. The recommendations are based on the user’s
previous search results.

Airline Route Planning : By using data science they can predict flight delay, decide which
class of airplanes to buy, whether to directly land at the destination or take a halt in between
(For example: A flight can have a direct route from New Delhi to New York. Alternatively, it
can also choose to halt in any country.) . Southwest Airlines, Alaska Airlines uses Data
Science.

Depending on your interests there are many different positions, companies and fields which touch
data science. You can use data science to analyze language, recommend videos, or to determine new
products from customer or marketing data.

Data Scientists

Data Scientists are those who perform data science. A Data scientist performs research and analyses
data and help companies flourish by predicting growth, trends and business insights based on a
large amount of data. Basically, data scientists are big data wranglers. They take this huge data and
use their skills in mathematics, statistics and programming to clean and organise the data. All their
analysis combined with industrial knowledge helps to uncover hidden solutions to business
challenges.